An embodiment of the present invention provides a method for generating estimates of flows between nodes in an economic network as discovered by a plurality of public and private sources (i.e., United States Security and Exchange Commission (SEC) documents and filings, press releases, company presentations, websites, interviews, analyst estimates, etc. and their foreign equivalents), seeking to specify a value over a specific timeframe for the interaction between each pair of economic entities. These entities can be interpreted to be general actors in a network, whether that is companies, firms, divisions, persons, sectors, etc. as long as reasonably and functionally equivalent units are used for each entity. Similarly, the flows between entities can be interpreted as general interactions between entities, whether that is goods, services, monies, information, economic traffic, dollars, euros, etc. as long as the unit chosen provides a meaningful measure of relative comparison. While the present disclosure is focused on financial relationships between global companies, the present invention can take many forms and can be configured to apply to a wide range of situations and to a wide range of applicable entities.
Due to the private nature of many economic activities and limited public record requirements, full access to customer, supplier, debtor, creditor, partner, distributor, etc. agreements is not generally possible. For example, in the United States, the SEC currently only requires companies to disclose any relationships that comprise more than 10% of their revenue in a given reporting period. This places an analyst in the position of having summary statistics from the network with only a partial view into the network's details and the relative magnitude of an entity's interaction with its neighbors.
However, most of the network analytics that would be useful in establishing the importance of an entity require a complete characterization of the internal network, meaning that each relationship should have a value assigned to it. This is true for all measures of advanced analysis such as centrality measurements, including eigenvector, closeness, betweenness, weighted degree, etc. Only a very small subset of network statistics can be completed with binary relationship information, and those would be largely static since binary economic relationships do not tend to change on a daily or monthly basis.